Heather's PhD graduation ceremony was today. She
has
two
of
three signatures, and still needs to submit an archival
copy, but otherwise is basically done. I am so proud of her.

The valedictory speech by Daniel Hernandez (also
known
as
the editor of the Daily Cal) was very good. Prof. Christ's
speech was also good. Prof. Adelman's speech was not bad,
but had a somewhat defensive tone regarding the importance
of English vs other more ostensibly practical pursuits,
including a potshot at computer science.

Heather's father and youngest sister were there,
as
were
the
kids and I. Also, Marty and Jan. Jan seemed offended that I
shook her hand in parting (as opposed to a hug). Oh well.

Low tech trust vs. high tech trust

I had an interesting discussion with Roger
Dingledine
and Luke (hacker-name armitage) over lunch at ETCon about
the importance
of
manual input into attack-resistant trust metrics. Advogato
uses the explicit,

"Low tech trust" is a pattern of manual information flow
across trust links. Example: links to recommended content,
represented by "hot lists" in the early days of the Web,
blogrolling today. You can find a well recommended blog by
starting with one you know, and clicking blogroll links.
Google's PageRank calculates something similar.

Example: personal music recommendations. Automated
recommendation systems (Firefly, Amazon) don't work as well
as just getting recommendations from friends.

Both examples are attack-resistant, borrowing the analysis
from trust metrics. In blog rolls, trust graph is explicit.
In music recommendations, trust graph is implicit in flow of
recommendations (they only flow between friends).

Low tech trust is good. Automated computation is harder, but
opens interesting doors. Example: manual clicking on links
is good at finding high quality random site, but Google is
good at finding high quality site relevant to search term
(and quickly, too). Killer apps for trust metrics will
probably follow the same pattern.